Tag Archives: Akka

Anyone who has done multithreading in the past won’t deny how hard and painful it is to manage multithreaded applications. I said manage because it starts out simple and it became a whole lot of fun once you start seeing performance improvements. However, it aches when you see that you don’t have a easier way to recover from errors in ...

I like the JVM a lot because there are a lot of tools available for inspecting a running JVM instance at runtime. The Java Mission Control (jmc) is one of my favorite tools, when it comes to monitor threads, hot methods and memory allocation. However these tools are of limited use, when monitoring an event-driven, message-based system like Akka. A ...

This article will show you how to build docker images that contain a single akka cluster application. You will be able to run multiple seed nodes and multiple cluster nodes. The code can be found on Github and will be available as a Typesafe Activator. If you don’t know docker or akka Docker is the new shiny star in the devops world. ...

Some time ago I wrote how to implement a reactive message queue with Akka Streams. The queue supports streaming send and receive operations with back-pressure, but has one downside: all messages are stored in-memory, and hence in case of a restart are lost. But this can be easily solved with the experimental akka-persistence module, which just got an update in ...

Event here, event there, events flying everywhere. Post about checking that every Akka event will finally find its home. Akka and reactive, event-based applications are new approach to creating software. We are using Akka pretty intensively in our current Scala-based project. Events fit our use cases especially well as we are communicating with external API which might be slow. This ...

Reactive streams is a recently announced initiative to create a standard for asynchronous stream processing with built-in back-pressure, on the JVM. The working group is formed by companies such as Typesafe, Red Hat, Oracle, Netflix, and others. One of the early, experimental implementations is based on Akka. Preview version 0.3 includes actor producers & consumers, which opens up some new ...

My colleagues are developing a trading system that processes quite heavy stream of incoming transactions. Each transaction covers one Instrument (think bond or stock) and has some (now) unimportant properties. They are stuck with Java (< 8), so let’s stick to it: class Instrument implements Serializable, Comparable<Instrument> { private final String name; public ...

We are designing a large scale distributed event-driven system for real-time data replication across transactional databases. The data(messages) from the source system undergoes a series of transformations and routing-logic before reaching its destination. These transformations are multi-process and multi-threaded operations, comprising of smaller stateless steps and tasks that can be performed concurrently. There is no shared state across processes instead, the state transformations ...

The release of 2.3.0 version of Akka toolkit was recently announced. Akka is a very useful toolkit and runtime for building highly concurrent, distributed, and fault tolerant event-driven applications on the JVM. It is distributed and provides high-level abstractions like Actors, Futures and STM. Its new release comes eight months after the 2.2.0 release and brings along new features. One ...

Imagine a simple Akka actor system consisting of two parties: MonitoringActor and NetworkActor. Whenever someone (client) sends CheckHealth to the former one it asks the latter by sending Ping. NetworkActor is obligated to reply with Pong as soon as possible (scenario [A]). Once MonitoringActor receives such a reply it immediately replies to the client with Up status message. However MonitoringActor ...

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